Reducing trace recording overheads with targeted recording via partial snapshots

ABSTRACT

Performing a targeted partial recording of an executable entity includes executing the executable entity at a processor. While executing the executable entity, it is determined that a target chunk of executable instructions are to be executed as part of the execution of the executable entity. Each input to the target chunk of executable instructions is identified, including identifying at least one non-parameter input. A corresponding value for each identified input is recorded into a trace, along with information identifying the target chunk of executable instructions.

CROSS-REFERENCE TO RELATED APPLICATIONS

Not Applicable.

BACKGROUND

Tracking down and correcting undesired software behaviors is a coreactivity in software development. Undesired software behaviors caninclude many things, such as execution crashes, runtime exceptions, slowexecution performance, incorrect data results, data corruption, and thelike. Undesired software behaviors might be triggered by a vast varietyof factors such as data inputs, user inputs, race conditions (e.g., whenaccessing shared resources), etc. Given the variety of triggers,undesired software behaviors can be rare and seemingly random, andextremely difficult reproduce. As such, it can be very time-consumingand difficult for a developer to identify a given undesired softwarebehavior. Once an undesired software behavior has been identified, itcan again be time-consuming and difficult to determine its rootcause(s).

Developers have conventionally used a variety of approaches to identifyundesired software behaviors, and to then identify the location(s) in anapplication's code that cause the undesired software behavior. Forexample, a developer might test different portions of an application'scode against different inputs (e.g., unit testing). As another example,a developer might reason about execution of an application's code in adebugger (e.g., by setting breakpoints/watchpoints, by stepping throughlines of code, etc. as the code executes). As another example, adeveloper might observe code execution behaviors (e.g., timing,coverage) in a profiler. As another example, a developer might insertdiagnostic code (e.g., trace statements) into the application's code.

While conventional diagnostic tools (e.g., debuggers, profilers, etc.)have operated on “live” forward-executing code, an emerging form ofdiagnostic tools enable “historic” debugging (also referred to as “timetravel” or “reverse” debugging), in which the execution of at least aportion of a program's thread(s) is recorded into one or more tracefiles (i.e., a recorded execution). Using some tracing techniques, arecorded execution can contain “bit-accurate” historic trace data, whichenables the recorded portion(s) the traced thread(s) to be virtually“replayed” (e.g., via emulation) down to the granularity of individualinstructions (e.g., machine code instructions, intermediate languagecode instructions, etc.). Thus, using “bit-accurate” trace data,diagnostic tools can enable developers to reason about a recorded priorexecution of subject code, as opposed to a “live” forward execution ofthat code. For example, a historic debugger might provide userexperiences that enable both forward and reversebreakpoints/watchpoints, that enable code to be stepped through bothforwards and backwards, etc. A historic profiler, on the other hand,might be able to derive code execution behaviors (e.g., timing,coverage) from prior-executed code.

As an example, a tracer might emulate execution of a subject thread,while recording information sufficient to reproduce initial processorstate for at least one point in a thread's prior execution (e.g., byrecording a snapshot of processor registers), along with the data valuesthat were read by the thread's instructions as they executed after thatpoint in time (e.g., the memory reads). This bit-accurate trace can thenbe used to replay execution of the thread's code instructions (startingwith the initial processor state) based on supplying the instructionswith the recorded reads. Such trace recording can introduce significantoverheads on execution of the subject thread or threads. For instance,to accomplish recording of a thread, the thread may need to be executedvia emulation, rather than directly on a processor, in order to observeand record the thread's reads from memory and/or registers.

Additionally, significant challenges arise when recording multi-threadedapplications in this manner, since those threads can interact with oneanother via shared memory. In order to overcome these challenges, manytrace recorders emulate multiple threads of an application by executingeach thread one-by-one in a linear, rather than a parallel,manner—essentially forcing these applications to executesingle-threaded. While this eliminates many of the challenges arisingfrom recording multi-threaded applications, it imposes a significantperformance penalty on those applications—both in terms of executingthem one thread at a time, and in terms of executing them via emulationrather than directly on a processor.

BRIEF SUMMARY

At least some embodiments described herein reduce the overheads of tracerecording by performing a limited recording of an entity (e.g., aprocess, a thread, etc.) based on recording only targeted code portionsof the entity. These targeted recording techniques rely on identifyingall of the inputs to a targeted code portion, and using a snapshot ofthose inputs to record the targeted code portion. These targetedrecording techniques can eliminate the need to emulate execution of anyportion of the entity during trace recording, or reduce the overheads ofemulation if it is performed, while still providing the ability toreplay execution of the targeted portion(s) of the entity later. Inembodiments, these targeted recording techniques balance a tradeoffbetween reducing tracing overheads with the absolute accuracy of theresulting trace.

Some embodiments are directed to performing a targeted partial recordingof an executable entity. These embodiments execute the executable entityat a processor. While executing the executable entity, these embodimentsdetermine that a target chunk of executable instructions are to beexecuted as part of the execution of the executable entity. Theseembodiments identify each input to the target chunk of executableinstructions, including identifying at least one non-parameter input,and then record a corresponding value for each identified input into atrace, along with information identifying the target chunk of executableinstructions.

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the invention can be obtained, a moreparticular description of the invention briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only typical embodiments of the invention and are not thereforeto be considered to be limiting of its scope, the invention will bedescribed and explained with additional specificity and detail throughthe use of the accompanying drawings in which:

FIG. 1A illustrates an example computing environment that facilitatesperforming targeted partial recordings of executable entities;

FIG. 1B illustrates an example tracing component that performs a limitedrecording of an entity based on recording only targeted code portions ofthe entity; and

FIG. 2 illustrates an example of forking a thread to verify if a datarace occurred on an original thread;

FIG. 3 illustrates an example of priming a cache as part of performingan emulation of a target code portion, and of deferred cache entryvalidation; and

FIG. 4 illustrates a flow chart of an example method for performing atargeted partial recording of an executable entity.

DETAILED DESCRIPTION

At least some embodiments described herein reduce the overheads of tracerecording by performing a limited recording of an entity (e.g., aprocess, a thread, etc.) based on recording only targeted code portionsof the entity. These targeted recording techniques rely on identifyingall of the inputs to a targeted code portion, and using a snapshot ofthose inputs to record the targeted code portion. These targetedrecording techniques can eliminate the need to emulate execution of anyportion of the entity during trace recording, or reduce the overheads ofemulation if it is performed, while still providing the ability toreplay execution of the targeted portion(s) of the entity later. Inembodiments, these targeted recording techniques balance a tradeoffbetween reducing tracing overheads with the absolute accuracy of theresulting trace.

Some embodiments trace a targeted code portion by identifying each inputconsumed by the targeted code portion, and by recording a partialsnapshot comprising all of those inputs. These embodiments let thetargeted code portion execute normally—without emulating the targetedcode portion—which greatly reduces the overheads of recording the codeportion as compared to prior techniques. The traced code portion can bereplayed via emulation later, based on supplying it with the recordedinputs. In multithreaded recording environments, a recording of a targetcode portion executing on a first thread that is recorded using thesetechniques could potentially miss recording of an interference by asecond thread (e.g., if the second thread modifies one or more of thetarget code portion's inputs). To address these situations, embodimentsmight use one or more techniques to detect when a recording of a targetcode portion does not accurately capture the code portion's actualexecution at recording time.

For example, one technique might fork the executing entity duringrecording, causing a forked entity to execute a copy of code portionusing a memory space that is separate from a memory space used by theoriginal entity and original code portion. Since the forked entity isexecuting in a separate memory space, any interference by other threadsto the original code portion's inputs should not occur to the forkedcopy of the code portion's inputs. This technique can then compare theoutputs of executing the original code portion with the outputs ofexecuting the forked code portion. If the outputs are the same, therewas likely no interference from other threads, or if there wasinterference that interference had no effect on the code portion'soutputs. Thus, the recording of that code portion might be deemedtrustworthy. If the outputs differ, there was likely an interferencefrom other threads that affected the code portion's outputs, and therecording of that code portion might be deemed untrustworthy.

Another technique might record, into the trace, information indicativeof the target code portion's outputs. For instance, this technique mightrecord the value of each output, record a hash of each output, record ahash over a plurality of outputs, etc. Then, after a later replay of thetarget code portion based on the recorded inputs snapshot, thesetechniques can compare the output(s) generated by the target codeportion during replay with the recorded information indicative of thetarget code portion's outputs. If they are the same, then the replaymight be deemed to reliably represent the original execution. If theyare not, then the replay might be deemed to unreliable.

Another technique might record, into the trace, information at leastpartially indicative of processor state during execution of the targetcode portion. For example, information indicative of processor statecould include at least a portion of a control flow trace (sometimes alsoreferred to as a branch trace). For instance, a control flow trace couldcomprise a trace generated by INTEL Processor Trace (IPT) or similartechnologies. Then, during replay of the target code portion, thiscontrol flow trace could be compared to control flow observed during thereplay to determine whether or not the replayed code flow matches theoriginal code flow (and, by extension, whether or not the replay isreliable). As another example, information indicative of processor statecould include occasional snapshots(s) of at least a portion of processorstate (e.g., a copy or a hash of one or more processor registers). Then,during replay of the target code portion, these snapshot(s) can becompared to processor state generated during replay to determine whetheror not the replayed processor state matches the original processor state(and, by extension, whether or not the replay is reliable). As anotherexample, information indicative of processor state could includeoccasional processor event-based samples. For instance, an event samplecould comprise samples generated using INTEL Processor Event-BasedSample (PEBS) or similar technologies. Then, during replay of the targetcode portion, these samples can be compared to processor samplesgenerated during replay to determine whether or not the replayed samplesmatch the original samples (and, by extension, whether or not the replayis reliable).

Other embodiments might also emulate a targeted code portion to capturea bit-accurate trace of the targeted code portion, but leverage theidentified input(s) to the targeted code portion to reduce the overheadsof performing that emulation as compared to conventional emulation-basedrecording techniques. In embodiments, overheads of performing theemulation are reduced by using the identified input(s) to prime a cache(e.g., processor cache, emulate cache, etc.) with the inputs needed bythe targeted code portion prior to emulating the code portion. In thisway, cache misses on memory corresponding to the identified inputs areavoided during the emulation, increasing emulation performance.Additional embodiments might further defer validating these primed cacheentries against a backing memory when the targeted code portion accessesa cache entry during emulation, further increasing emulationperformance.

To the accomplishment of the foregoing, FIG. 1A illustrates an examplecomputing environment 100 a that facilitates performing targeted partialrecordings of executable entities. As depicted, computing environment100 a may comprise or utilize a special-purpose or general-purposecomputer system 101, which includes computer hardware, such as, forexample, one or more processors 102, system memory 103, durable storage104, and/or network device(s) 105, which are communicatively coupledusing one or more communications buses 106.

Embodiments within the scope of the present invention can includephysical and other computer-readable media for carrying or storingcomputer-executable instructions and/or data structures. Suchcomputer-readable media can be any available media that can be accessedby a general-purpose or special-purpose computer system.Computer-readable media that store computer-executable instructionsand/or data structures are computer storage media. Computer-readablemedia that carry computer-executable instructions and/or data structuresare transmission media. Thus, by way of example, and not limitation,embodiments of the invention can comprise at least two distinctlydifferent kinds of computer-readable media: computer storage media andtransmission media.

Computer storage media are physical storage media (e.g., system memory103 and/or durable storage 104) that store computer-executableinstructions and/or data structures. Physical storage media includecomputer hardware, such as RAM, ROM, EEPROM, solid state drives(“SSDs”), flash memory, phase-change memory (“PCM”), optical diskstorage, magnetic disk storage or other magnetic storage devices, or anyother hardware storage device(s) which can be used to store program codein the form of computer-executable instructions or data structures,which can be accessed and executed by a general-purpose orspecial-purpose computer system to implement the disclosed functionalityof the invention.

Transmission media can include a network and/or data links which can beused to carry program code in the form of computer-executableinstructions or data structures, and which can be accessed by ageneral-purpose or special-purpose computer system. A “network” isdefined as one or more data links that enable the transport ofelectronic data between computer systems and/or modules and/or otherelectronic devices. When information is transferred or provided over anetwork or another communications connection (either hardwired,wireless, or a combination of hardwired or wireless) to a computersystem, the computer system may view the connection as transmissionmedia. Combinations of the above should also be included within thescope of computer-readable media.

Further, upon reaching various computer system components, program codein the form of computer-executable instructions or data structures canbe transferred automatically from transmission media to computer storagemedia (or vice versa). For example, computer-executable instructions ordata structures received over a network or data link can be buffered inRAM within a network interface module (e.g., network device(s) 105), andthen eventually transferred to computer system RAM (e.g., system memory103) and/or to less volatile computer storage media (e.g., durablestorage 104) at the computer system. Thus, it should be understood thatcomputer storage media can be included in computer system componentsthat also (or even primarily) utilize transmission media.

Computer-executable instructions comprise, for example, instructions anddata which, when executed at one or more processors, cause ageneral-purpose computer system, special-purpose computer system, orspecial-purpose processing device to perform a certain function or groupof functions. Computer-executable instructions may be, for example,machine code instructions (e.g., binaries), intermediate formatinstructions such as assembly language, or even source code.

Those skilled in the art will appreciate that the invention may bepracticed in network computing environments with many types of computersystem configurations, including, personal computers, desktop computers,laptop computers, message processors, hand-held devices, multi-processorsystems, microprocessor-based or programmable consumer electronics,network PCs, minicomputers, mainframe computers, mobile telephones,PDAs, tablets, pagers, routers, switches, and the like. The inventionmay also be practiced in distributed system environments where local andremote computer systems, which are linked (either by hardwired datalinks, wireless data links, or by a combination of hardwired andwireless data links) through a network, both perform tasks. As such, ina distributed system environment, a computer system may include aplurality of constituent computer systems. In a distributed systemenvironment, program modules may be located in both local and remotememory storage devices.

Those skilled in the art will also appreciate that the invention may bepracticed in a cloud computing environment. Cloud computing environmentsmay be distributed, although this is not required. When distributed,cloud computing environments may be distributed internationally withinan organization and/or have components possessed across multipleorganizations. In this description and the following claims, “cloudcomputing” is defined as a model for enabling on-demand network accessto a shared pool of configurable computing resources (e.g., networks,servers, storage, applications, and services). The definition of “cloudcomputing” is not limited to any of the other numerous advantages thatcan be obtained from such a model when properly deployed.

A cloud computing model can be composed of various characteristics, suchas on-demand self-service, broad network access, resource pooling, rapidelasticity, measured service, and so forth. A cloud computing model mayalso come in the form of various service models such as, for example,Software as a Service (“SaaS”), Platform as a Service (“PaaS”), andInfrastructure as a Service (“IaaS”). The cloud computing model may alsobe deployed using different deployment models such as private cloud,community cloud, public cloud, hybrid cloud, and so forth.

Some embodiments, such as a cloud computing environment, may comprise asystem that includes one or more hosts that are each capable of runningone or more virtual machines. During operation, virtual machines emulatean operational computing system, supporting an operating system andperhaps one or more other applications as well. In some embodiments,each host includes a hypervisor that emulates virtual resources for thevirtual machines using physical resources that are abstracted from viewof the virtual machines. The hypervisor also provides proper isolationbetween the virtual machines. Thus, from the perspective of any givenvirtual machine, the hypervisor provides the illusion that the virtualmachine is interfacing with a physical resource, even though the virtualmachine only interfaces with the appearance (e.g., a virtual resource)of a physical resource. Examples of physical resources includingprocessing capacity, memory, disk space, network bandwidth, mediadrives, and so forth.

As shown in FIG. 1A, each processor 102 can include (among other things)one or more processing units 107 (e.g., processor cores) and one or morecaches 108. Each processing unit 107 loads and executes machine codeinstructions via the caches 108. During execution of these machine codeinstructions at one more execution units 107 b, the instructions can useinternal processor registers 107 a as temporary storage locations andcan read and write to various locations in system memory 103 via thecaches 108. In general, the caches 108 temporarily cache portions ofsystem memory 103; for example, caches 108 might include a “code”portion that caches portions of system memory 103 storing applicationcode, and a “data” portion that caches portions of system memory 103storing application runtime data. If a processing unit 107 requires data(e.g., code or application runtime data) not already stored in thecaches 108, then the processing unit 107 can initiate a “cache miss,”causing the needed data to be fetched from system memory 103—whilepotentially “evicting” some other data from the caches 108 back tosystem memory 103.

As illustrated, the durable storage 104 can store computer-executableinstructions and/or data structures representing executable softwarecomponents; correspondingly, during execution of this software at theprocessor(s) 102, one or more portions of these computer-executableinstructions and/or data structures can be loaded into system memory103. For example, the durable storage 104 is shown as potentiallystoring computer-executable instructions and/or data structurescorresponding to a tracing component 109, a debugging component 110, anemulation component 111, and one or more application(s) 112. The durablestorage 104 can also store data, such as one or more recordedexecution(s) 113 (e.g., traces of application(s) 112 that are generatedusing historic debugging technologies).

In general, the tracing component 109 records or “traces” execution ofone or more of application(s) 112 into the recorded execution(s) 113.The tracing component 109 can record execution of application(s) 112whether that execution be a “live” execution on the processor(s) 102directly, whether that execution be a “live” execution on theprocessor(s) 102 via a managed runtime, and/or whether that execution bean emulated execution via the emulation component 111. Thus, FIG. 1Aalso shows that the tracing component 109 is also loaded into systemmemory 103 (i.e., tracer component 110′). An arrow between tracingcomponent 109′ and recorded execution(s) 113′ indicates that the tracingcomponent 109′ can record trace data into recorded execution(s) 113′(which might then be persisted to the durable storage 104 as recordedexecution(s) 113). The tracing component 109 can correspond to any typeof tool that records a recorded execution 113 as part of execution oremulation of an application 112. For instance, the tracing component 109might be part of a hypervisor, an operating system kernel, a debugger, aprofiler, etc. As will be explained in more detail in connection withFIG. 1B, in accordance with the embodiments herein the tracing component109 can reduce the overheads of trace recording by performing a limitedrecording of an entity based on recording only targeted code portions ofthe entity.

In general, the debugging component 110 leverages the emulationcomponent 111 in order to emulate execution of code of executableentities, such as application(s) 112, based on execution state dataobtained from one or more of the recorded execution(s) 113. Thus, FIG.1A shows that the debugging component 110 and the emulation component111 are loaded into system memory 103 (i.e., debugging component 110′and emulation component 111′), and that the application(s) 112 are beingemulated within the emulation component 111′ (i.e., application(s)112′). The debugging component 110 can correspond to any type of toolthat consumes a recorded execution 113 as part of analyzing a priorexecution of an application 112. For instance, the debugging component109 might be a debugger, a profiler, a cloud service, etc.

It is noted that, while the tracing component 109, the debuggingcomponent 110, and/or the emulation component 111 might each beindependent components or applications, they might alternatively beintegrated into the same application (such as a debugging suite), ormight be integrated into another software component—such as an operatingsystem component, a hypervisor, a cloud fabric, etc. As such, thoseskilled in the art will also appreciate that the invention may bepracticed in a cloud computing environment of which computer system 101is a part. For instance, while these components 109-111 might take theform of one or more software applications executed at a user's localcomputer, they might also take the form of a service provided by a cloudcomputing environment.

It was mentioned previously that, in embodiments, the tracing component109 can provide functionality for reducing the overheads of tracerecording by performing a limited recording of an entity based onrecording only targeted code portions of the entity. To demonstrate howthe tracing component 109 might accomplish the foregoing embodiments,FIG. 1B illustrates an example 100 b of a tracing component 109 that isconfigured to perform limited recordings of entities based on recordingonly targeted code portions of the entity using knowledge of inputs tothose targeted code portions.

The depicted tracing component 109 in FIG. 1B includes a variety ofcomponents (e.g., inputs/outputs identification 114, executionsupervision 115, target recording 116, etc.) that represent variousfunctions that the tracing component 109 might implement in accordancewith various embodiments described herein. It will be appreciated thatthe depicted components—including their identity, sub-components, andarrangement—are presented merely as an aid in describing variousembodiments of the tracing component 109 described herein, and thatthese components are non-limiting to how software and/or hardware mightimplement various embodiments of the tracing component 109 describedherein, or of the particular functionality thereof.

In general, the tracing component 109 performs a limited recording of anentity based on an identification of inputs to targeted code portions tothat entity. In embodiments, a targeted code portion comprises a chunkof a sequence of executable instructions that consume zero or moreinputs and that produce one or more outputs. A targeted chunk ofexecutable instructions could comprise, for example, one or morefunctions, one or more modules, one or more basic blocks, a sequence ofinstructions between thread synchronization events, a sequence ofinstructions between thread transitions, etc. In embodiments, it ispossible for a targeted chunk of instructions to include sequences ofinstructions that have one or more gaps within their execution. Forexample, a chunk of instructions might include a sequence ofinstructions that make a kernel call in the middle of their execution.In this case, the gap might be dealt with by recording any side effectsof having executed the kernel call (e.g., by recording memory locationsand registers modified by the kernel call). Alternatively, the gap mightbe avoided by dividing the chunk into two different chucks—one includingthe instruction(s) before the gap and one including the instruction(s)after the gap. As shown, the tracing component 109 can include aninputs/outputs identification component 114 that can analyze an entityin order to identify all inputs to chunks of instructions that will, orcould, be targeted for trace recording. Optionally, the inputs/outputsidentification component 114 might also identify all outputs from thosechunks of instructions.

As used herein, an “input” to a chunk of instructions is defined as anydata location from which the chunk of instructions reads, and to whichthe chunk itself has not written prior to the read. These data locationscould include, for example, registers as they existed the time the chunkwas entered, and/or any memory location from which the chunk reads andwhich it did not itself allocate. An edge case may arise if a chunkallocates memory and then reads from that memory prior to writing to it(i.e., a read from uninitialized memory). In these instances,embodiments might either treat the read to uninitialized memory as aninput, or as a bug.

It is noted that, by the foregoing definition, the “inputs” to a chunkof instructions is more expansive than just those parameters that arepassed to that chunk. For instance, if a chunk of instructionscorresponds to a function, the chunk's inputs would include each memoryand/or register location corresponding to each parameter passed to thefunction (if any) and which are read by the function. However, inaddition, the chunk's inputs would also include such things as memoryand/or register locations corresponding to global variables that areread by the function, and memory and/or register locations derived fromother inputs and which are read by the function. For example, if aninput to a function includes a reference to the beginning of an array ora linked list, each element of that array or linked list that is read bythe function is also an input to the function. As another example, if aninput to a function comprises pointer to a memory address, any memorylocation that is read by the function based on an offset from thatmemory address is also an input to the function.

As used herein, an “output” is defined as any data location (e.g.,register and/or memory location) to which the chunk of instructionswrites that it does not later deallocate. As examples, outputs caninclude global variables written to by the chunk, memory locationswritten to by the chunk based on a pointer passed to the chunk, functionreturn values (i.e., if the chunk corresponds to a function), and thelike. Notably, a stack allocation at entry of the chunk, followed by awrite by the chunk to the allocated area, followed by a stackdeallocation at exit from the chunk, and thus could be excluded as anoutput for the chunk, since that memory was deallocated by the chunk. Inaddition, if a chunk is delimited by application binary interface (ABI)boundaries (e.g., if the chunk corresponds to a function), then anyvolatile registers (i.e., registers not used to pass a return value) atexit are implicitly “deallocated” (i.e., they are discarded by theABI)—and could be excluded as outputs for the chunk.

Notably, the identified inputs and/or outputs could be more expansivethan just the locations meeting the foregoing definitions. For example,implementations might treat all written named locations as outputs froma chunk (even if they are deallocated by the chunk) as these written-tolocations would be a superset of the outputs meeting the foregoingdefinition of an output, or might treat all read named locations asinputs to a chunk as these read-from locations would be a superset ofall the inputs meeting foregoing definition of an input. It might beless computationally-intensive to identify inputs/outputs when usingbroader definitions of inputs and/or outputs, with the tradeoff ofneeding to track more locations which might not strictly beinputs/outputs and which can result in larger snapshots.

In embodiments, the inputs/outputs identification component 114 mighttake as input an identity of one or more targeted chunk(s) ofinstructions (e.g., by a named reference such as a function or modulename, by instruction address range, etc.) and identify inputs/outputsfor only those identified chunk(s) of instructions. However, inembodiments the inputs/outputs identification component 114 mightalternatively identify different chunk(s) of instructions in the entityautomatically, and then identify inputs/outputs for each identifiedchunk of instructions. For example, the inputs/outputs identificationcomponent 114 might identify chunks corresponding to each function in anentity, and then identify inputs/outputs for each of those functions. Aspotentially more granular example, the inputs/outputs identificationcomponent 114 might alternatively identify chunks corresponding to eachbasic block in an entity, and then identify inputs/outputs for each ofthose basic blocks. Of course, the inputs/outputs identificationcomponent 114 could use many other techniques to automatically identifychunks, and these examples are for illustrative purposes only.

In embodiments, the inputs/outputs identification component 114 operatesprior to, and separate from, a tracing session. Thus, the inputs/outputsidentification component 114 can operate in an “offline” mode that isseparate from any actual tracing process. However, is also possible tofor the inputs/outputs identification component 114 to operate in an“online” mode during a tracing session. For instance, the inputs/outputsidentification component 114 might operate at initiation of a tracingsession, but prior to performing any tracing, to identify inputs/outputsfor one or more portion(s) of an entity. Alternatively, theinputs/outputs identification component 114 might operate on-demand whena targeted chunk of instructions is identified for execution andtracing.

The inputs/outputs identification component 114 can perform one or moretypes of analysis to identify inputs to a given chunk of instructionsand/or outputs from chunk of instructions. In one type of analysis, theinputs/outputs identification component 114 might perform a staticanalysis of the instructions of the chunk (and of other chunks, ifneeded for context) to determine which memory and/or register locationsthe chunk can read from and/or which memory and/or register locationsthe chunk can write to. In another type of analysis, the inputs/outputsidentification component 114 might perform a runtime analysis of theinstructions of the chunk (and of other chunks, if needed for context).This type of runtime analysis might, for example, be based onemulating/replaying that chunk based on one or more prior recordedexecutions 113 of that chunk. In another type of analysis, theinputs/outputs identification component 114 might perform a staticanalysis of one or more recorded executions 113 of the chunk. As will beappreciated by one of ordinary skill in the art, number and location ofthe inputs that a given chunk of instructions consumes, and the numberand location of the outputs that a given chunk of instructions writesto, might vary from one instance to another based on the values of theinputs. As such, runtime and/or static analysis of recorded executions113 might be particularly useful to produce a comprehensive list ofinputs and outputs, particularly as a number of the recorded executions113 analyzed increases. In embodiments, debugging symbols and/or codeannotations might additionally, or alternatively, be used to identifyinputs and/or outputs. For instance, embodiments might leverage NATVIStype descriptors, SAL annotations, code contracts, and the like.

In some implementations, the inputs/outputs identification component 114might alternatively identify the inputs and/or outputs of a chunk'sinstructions by instrumenting those instructions (e.g., viainstrumentation of source code from which the instructions werecompiled, or via instrumentation of the executable instructionsdirectly) so that that inputs and/or outputs are identified by theinstrumented instructions during their execution (or emulation). Forinstance, instrumentations might cause each read and/or write by theseinstructions to be trapped, so that the locations that are subject tothe read and/or write can be logged while handling the trap.

In embodiments, the inputs/outputs identification component 114 can usevarying levels of granularity when identifying inputs and outputs. Forexample, the inputs/outputs identification component 114 mightgranularly determine that the memory corresponding to a given input oroutput is a particular number of bits starting at a particular memoryaddress. Alternatively, the inputs/outputs identification component 114might less granularly determine that memory corresponding to a giveninput or output is the memory covered by a cache line that was accessedwhen reading the input (or writing to the output), that memorycorresponding to a given input is a memory page was accessed whenreading the input (or writing to the output), etc. As will beappreciated, a more granular identification of inputs and/or outputs canresult in smaller snapshots of a chunk's inputs than a less granularidentification of inputs. However, a performing a more granularidentification of inputs and/or outputs can also take more compute timeand resources than a less granular identification of inputs. As such,implementation of the inputs/outputs identification component 114 mightchoose a tradeoff between granularity and use of compute resources.

The execution supervision component 115 can observe and control a targetentity's execution at the processor(s) 102. If the target entitycomprises native code, the execution supervision component 115 mightobserve and interact with the entity directly. If the target entitycomprises managed code, the execution supervision component 115 mightadditionally, or alternatively, interact with a managed runtime. Inembodiments, the execution supervision component 115 might attach to acurrently-running instance of the target entity in order to trace theentity, and/or might initiate execution of the target entity in order totrace the entity.

The target recording component 116 operates to perform a limited,targeted, recording of an entity that is being supervised by theexecution supervision component 115, based on recording only targetedchunks of the entity. During a supervised execution of a target entityby the execution supervision component 115, the target identificationcomponent 117 can determine when a target chunk of executableinstructions are to be executed as part of the execution of theexecutable entity. For example, the target identification component 117might identify when a function, basic block, module, etc. of interest isto be executed as part of the entity. Then, based on the upcomingexecution of the target chunk of executable instructions, the inputsidentification component 118 identifies each input to that target chunk(e.g., input registers, memory locations, etc.).

In some embodiments, the inputs identification component 118 mightconsult inputs data that was previously generated by the inputs/outputsidentification component 114 (e.g., in an offline mode), while in otherembodiments, the inputs identification component 118 might call theinputs/outputs identification component 114 to have those inputsidentified for the identified target chunk of executable instructions(e.g., in an online mode). In some embodiments, the inputsidentification component 118 relies on execution of the target chunk ofexecutable instructions, themselves, for identification for the inputs.For example, the target chunk of executable instructions might have beenpreviously instrumented so that the instrumentations identify the inputsas they are read by the instrumented instructions.

Regardless of how the inputs were identified, the inputs recordingcomponent 119 can record a snapshot of those inputs into a recordedexecution 113, as part of a trace of the target chunk of executableinstructions. For example, the inputs recording component 119 canidentify a value for each input (e.g., by consulting the memorylocation(s) or register(s) corresponding to each input), and store anidentification of those memory location(s)/register(s), and theircorresponding value(s), into a recorded execution 113 of the targetentity. In embodiments, this snapshot data is stored along withinformation identifying the target chunk of executable instructions. Forinstance, this information could include a copy of the target chunk ofexecutable instructions, themselves, it could include a memory addressor memory address range corresponding to those instructions, it couldinclude an identification of the instructions by function or modulename, and the like.

For most chunks of instructions, recording a snapshot of the inputs tothe chunk is sufficient to fully and faithfully replay that chunk basedon the snapshot. As such, in embodiments, the target recording component116 concludes recording additional data for the target chunk ofexecutable instructions, and lets those instructions execute normally atthe processor(s) 102. As such, in these instances, the target recordingcomponent 116 has traced execution of that target chunk without actuallyemulating the instructions in the target chunk. Thus, while a relativelysmall amount of compute and memory/storage resources may have beenconsumed to create and store the snapshot, the tracing has had noadditional impact on execution of the instructions, themselves, at theprocessor(s) 102. Therefore, the overheads of recording thoseinstructions has been greatly reduced, as compared to prioremulation-based tracing techniques.

However, a snapshot of the inputs to a target chunk of instructions maysometimes not be sufficient to fully and faithfully replay that chunk ifanother entity (e.g., another thread in the same process) wrote to thatchunk's inputs during the chunk's execution at the processor(s) 102.These situations are commonly referred to as data races. In embodiments,the tracing component 109 may also record, into the recorded execution113, additional information usable to verify whether a data race mayhave affected execution of a target chunk of instructions in a mannerthat cannot be reproduced from the snapshot of its inputs.

For example, the target recording component 116 is shown as potentiallyincluding an outputs recording component 120. If included, the outputsrecording component 120 may also record, into the recorded execution113, information indicative of the output(s) that were generated by theexecution of the target chunk of executable instructions at theprocessor(s) 102. For example, the outputs recording component 120 mightrecord a snapshot of the output(s) (e.g., each output's memory addressor register name, and corresponding value), it might record a hash foreach output (e.g., a hash over the output's address/name and or itsvalue), it might record a hash over an aggregation of different outputs,and the like. Then, during replay, this information indicative of theoutput(s) can be compared to output data that is generated by replay ofthe target chunk of executable instructions based on the inputssnapshot. If the data does not match, then a data race probably occurredduring tracing of the target chunk, and the replay does not accuratelyrepresent what actually occurred during tracing. If the data does match,then the replay can be deemed reliable/trustworthy, at least as to theoutputs. Notably, matching output data may not conclusively indicatethat a data race did not occur during tracing, since a data race mighthave actually occurred during the execution of the chunk at theprocessor(s) 102, but that data race may have had no effect on theoutputs of the chunk.

As another example, the target recording component 116 is shown aspotentially including a processor state recording component 121. Ifincluded, the processor state recording component 121 may also record,into the recorded execution 113, information indicative of at least aportion of processor state while the target chunk executed at theprocessor(s) 102. For example, the processor state recording component121 might record all, or part, of a processor control flow trace. Alsoreferred to as a branch trace, a control flow trace is generallygenerated by a processor 102, itself, and records a record of whichcontrol flow instructions resulted a branch being taken or not taken.While many processor architectures support generation of control flowtraces, one example is INTEL's IPT. A recorded control flow trace for agiven chunk of instructions can be compared to the control flow taken bythose instructions during replay to determine if the replay accuratelyreproduces the original execution. Additionally, or alternatively, theprocessor state recording component 121 might record occasionalsnapshots of processor state. For instance, during execution of a targetchunk, the processor state recording component 121 might storeoccasional hashes based on processor registers at a given point inexecution, or record the actual values of those registers. Then, duringreplay of the target chunk, this recorded processor state can becompared to emulated processor state to determine if the replayaccurately reproduces the original execution. Additionally, oralternatively, the processor state recording component 121 might recordoccasional processor event-based samples in connection with execution ofa target chunk, such as those generated by technologies such as INTEL'sPEBS. Then, during replay of the target chunk, these recorded samplescan be compared to emulated samples to determine if the replayaccurately reproduces the original execution.

Notably, using any of the foregoing processor state, recorded processorstate might be usable, at replay time, to help estimate when/where amemory race occurred. For instance, if outputs generated during replaydon't match the outputs generated during tracing, embodiments mightidentify which output(s) are different and work backwards through thechunk of instructions to identify those instructions whose executionaffected (or could affect) each of those outputs. Using recordedprocessor state can reduce the search space of this analysis, by helpingto pinpoint where execution of those instructions diverged.

In other embodiments, the tracing component 109 actually verifies,during recoding, whether a data race affected execution of a targetchunk of instructions in a manner that cannot be reproduced from thesnapshot of its inputs alone. For instance, the target recordingcomponent 116 might take the outputs verification concept above evenfurther by verifying outputs itself during trace recording. For example,the target recording component 116 is shown as potentially including anexecution validation component 122. In embodiments, the executionvalidation component 122 creates a fork of the entity that is underobservation prior to executing the target chunk of instructions. Then,both the target entity and the fork of the target entity are permittedto execute their respective copy of the target chunk of instructions.

FIG. 2, for example, illustrates an example 200 representing a timelineof execution of related threads 201. In particular, thread 201 arepresents an entity that under observation by the execution supervisioncomponent 115. At execution time point 203 a, example 200 shows thatexecution of thread 201 a is forked (e.g., by the execution validationcomponent 122) to initiate execution of thread 201 a′. Execution timepoint 203 a might correspond, for example, to the beginning of executionof a target chunk of instructions that is begin traced by the targetrecording component 116. In embodiments, creating a fork of the entitycreates a separate memory space for the forked entity. Thus, thread 201a′ executes its copy of the target chunk of instructions using differenta memory space than thread 201 a, and is therefore isolated from dataraces occurring on thread 201 a. For example, arrow 202 shows that,during execution of the target chunk of instructions on forked thread201 a′, thread 202 b performs a write to memory used by thread 201 a.However, as shown, this write does not affect forked thread 201 a′.After execution of the target chunk of instructions, the executionvalidation component 122 can compare the outputs of target chunk ofinstructions generated by thread 201 a with the outputs of target chunkof instructions generated by forked thread 201 a′. For example, a lineat execution time point 203 b represents a comparison (e.g., by theexecution validation component 122) of the outputs of executing thetarget instructions on each of original thread 201 a and forked thread201 a′. If these outputs match, then the inputs snapshot generated bythe inputs recording component 119 can be deemed a reliablerepresentation of execution of the target chunk on thread 201 a; If theydon't match, however, then a data race probably occurred on thread 201 a(i.e., the write by thread 201 b at arrow 202), and the inputs snapshotcannot be deemed a reliable representation of execution of the targetchunk on thread 201 a. In this latter case, the target recordingcomponent 116 might record an indication that the recorded snapshot isunreliable, might choose not to record the snapshot, might raise analert, etc.

In embodiments, the execution validation component 122 can supportexecution of a chunk of instructions in a forked thread, even when thatchunk of instructions make a kernel call or a call to other non-tracedcode. For instance, the execution validation component 122 mightdetermine whether or not the call is idempotent (e.g., based on whetherit writes to any of the chunk's inputs and/or outputs). If the call isnon-idempotent, the execution validation component 122 might simplyallow the forked thread to make the call.

If the call is idempotent, however, the execution validation component122 might treat the chunk of instructions as two different chunks—afirst leading up to the call, and a second after the call. Thus, theinputs identification component 118 can identify inputs and outputs foreach of these chunks. Then, the execution validation component 122 cancompare the outputs of executing the first chunk in a forked thread withthe outputs of executing the first chunk in the original thread, andalso compare the outputs of executing the second chunk in a forkedthread with the outputs of executing the second chunk in the originalthread. In embodiments, the first and second chunks might be executed indifferent forked threads. However, it might also be possible to executethem in the same forked thread if the call takes the same inputs in boththe original and forked threads, by applying the side effects ofexecuting the call on the original thread (i.e., its writes) to thememory space of the forked thread prior to the second chunk's executionon the forked thread. If the precise set of inputs to the call cannot bedetermined, they might be able to be proxied as the inputs to the firstchunk plus the set of outputs produced by the first chunk in both forks.

In other embodiments, the execution validation component 122additionally, or alternatively, relies on use of page table entries(PTEs) to determine, during recording, if another thread interferes withthe thread being traced. In this embodiment, the execution validationcomponent 122 might even be able to identify the particular input(s)that were interfered with. In particular, the execution validationcomponent 122 can modify the PTEs for any pages corresponding to inputsto the target chunk of instructions as being protected—e.g., as beingvalid for the subject thread and invalid for other threads. Then, if anyother thread attempts to write to memory in those pages during executionof the target chunk of instructions on the subject thread, a page faultwill occur and a potential interference can be noted.

In embodiments, the execution validation component 122 could even usePTEs to determine if the subject thread tried to access a memorylocation that was not included in its list of identified inputs. Forexample, the execution validation component 122 can modify the PTEs forany pages not corresponding to inputs to the target chunk ofinstructions as being protected—e.g., as being invalid for the subjectthread. Then, if the subject thread attempts to access memory in thosepages during execution of the target chunk of instructions, a page faultwill occur and an access to memory not identified as an input can benoted.

In embodiments, the target recording component 116 might choose toactually emulate the target chunk of executable instructions. As such,the target recording component 116 is shown as potentially including anemulation component 123. In connection with emulation by the emulationcomponent 123, the target recording component 116 can record a detailedtrace of those instruction's execution. For example, a user might haveprovided an indication that the target chunk of executable instructionsshould be recorded with a greater level of detail (e.g., due to aparticular interest in the behaviors of that target chunk). As anotherexample, the target recording component 116 might determine (e.g., basedon the execution validation component 122) that a prior recording of thetarget chunk exhibited signs of a data race, triggering a more granulartrace of the current instance of the target chunk.

While emulation and recording of the target chunk will incur additionaloverheads verses simply letting the chunk execute normally at theprocessor(s) 102, the emulation component 123 can leverage knowledge ofthe chunk's inputs (i.e., as identified by the inputs identificationcomponent 118) to improve the performance of that emulation. Inembodiments, prior to emulating the target chunk, the emulationcomponent 123 primes a cache (e.g., cache(s) 108) with cache entriescovering memory addresses/values stored in the snapshot recorded by theinputs recording component 119. For example, FIG. 3 illustrates anexample 300 of priming a cache with inputs. In particular, example 300shows a portion of a memory 301 (e.g., system memory 103) and a portionof a cache 302 (e.g., cache(s) 108). In FIG. 3, memory locations 0x110through 0x160 and memory locations 0x1C0 through 0x1D0 have beenidentified by the emulation component 123 as corresponding to inputs toa target chunk of instructions. For example, these inputs mightcorrespond to four 32-bit variables, stored beginning at memoryaddresses 0x110, 0x130, 0x150, and 0x1C0. As shown, prior to emulatingthe target chunk of instructions, the emulation component 123 can primethe cache 302 with cache entries that cover these memory locations.Then, when the emulation component 123 emulates the target chunk ofinstructions, cache misses can be avoided when the target chunk ofinstructions accesses these memory locations, greatly speeding up thespeed of the emulation.

When a cache utilizes an existing cache entry, the cache may validatethe value stored in the cache entry against the cache's backing store(e.g., system memory 103) to ensure that the data in the cache entry iscurrent. In embodiments, after priming a cache, the emulation component123 causes these validations to be deferred—again, greatly speeding upthe speed of emulation. In embodiments, these deferrals are based on anassumption that the entity being recorded does not perform cross-threadcoordination (e.g., via shared memory with other threads) without firstproperly using cross-thread synchronization techniques (e.g., mutexes,semaphores, etc.). Thus, the emulation component 123 might cause thesevalidations to be deferred until the next cross-thread synchronizationevent. At a cross-thread synchronization event, the emulation component123 might cause the cache entries to be fully validated (e.g., byconfirming each one with system memory 103). Alternatively, theemulation component 123 might cause the cache entries to be lazilyvalidated. For example, in FIG. 3, the cache 302 is shown as including aflag for each cache entry. In embodiments, this flag can be used toindicate if the corresponding cache entry should be validated againstthe backing store the next time it is accessed. Thus, for example, theemulation component 123 might cause these flags to be cleared when acache entry is primed. Then, at a cross-thread synchronization event,the emulation component 123 might cause these flags to be set (at leastfor the primed cache entries). Later, if one of these cache entries isaccessed it can be validated against the backing store, updated ifneeded, and its flag can be cleared.

Notably, by priming a cache, the emulation component 123 can determine,at tracing time, if the identification of inputs to a given chunk ofinstructions actually included all of the inputs. For instance, afterpriming the cache for a given chunk of instructions, if execution of thetarget instructions results in a cache miss, the emulation component 123can determine that the memory accessed as part of the cache miss shouldhave been included as an input. This cache miss can be recorded toensure a complete trace, and the identification of inputs for that chunkof instructions can be updated to include this memory address.

In embodiments, the target recording component 116 might additionally,or alternatively, record a more granular execution of a chunk ofinstructions based on instrumentation of those instructions. Forexample, just as instructions might be instrumented to generate anidentification of their inputs (and/or outputs), they may additionally,or alternatively, be instrumented to generate a record of their reads(and the value read) and/or their writes (and/or the value written). Assuch, execution of an instrumented target chunk of instructions couldresult in generation of trace data that is then recorded into a recordedexecution 113.

FIG. 4 illustrates a flowchart of an example method 400 for performing atargeted partial recording of an executable entity. Method 400 will nowbe described within the context of with FIGS. 1-3. While, for ease indescription, the acts of method 400 are shown in a sequential linearorder, it will be appreciated that some of these acts might beimplemented in different orders, and/or in parallel.

As shown in FIG. 4, method 400 can include an act 401 of pre-processinginputs. In some embodiments, act 401 comprises pre-processing anexecutable entity to identify each input to one or more target chunks ofexecutable instructions. For example, the inputs/outputs identificationcomponent 114 can analyze a chunk of executable instructions of anapplication 112 to identify the chunk's inputs and/or its outputs. Act401 is shown in broken lines, since the act might be performed as partof a partial recording session (e.g., an “online” mode), or it might beperformed prior to that session (e.g., an “offline” mode). As discussedwhen describing the inputs/outputs identification component 114,identifying each input to the target chunk of executable instructionsmight be based on having performed at least one of (i) a static analysisof the target chunk of executable instructions, (ii) a static analysisof a recorded execution of the target chunk of executable instructions,(iii) an emulation of the target chunk of executable instructions, (iv)an instrumentation of the target chunk of executable instructions,and/or (v) an analysis of at least one of debugging symbols or codeannotations.

Method 400 also includes an act 402 of executing a subject entity. Insome embodiments, act 402 comprises executing the executable entity atthe at least one processor. For example, the execution supervisioncomponent 115 can supervise execution of one or more threads of anapplication 112 at processor(s) 102. In embodiments, the executionsupervision component 115 might initiate execution of application 112 aspart of method 400, or attach to an existing instance of an application112 already executing at processor(s) 102.

Method 400 also includes an act 403 of identifying a target chunk ofinstructions in the entity. In some embodiments, act 403 comprises,while executing the executable entity, determining that a target chunkof executable instructions are to be executed as part of the executionof the executable entity. For example, based on the supervision by theexecution supervision component 115, the target identification component117 can identify when a target chunk of instructions is to be executed.For instance, the target identification component 117 might identifywhen a particular function is to be executed, when an instruction at aparticular address is to be executed, etc.

Method 400 also includes an act 404 of identifying each input to thetarget chunk. In some embodiments, act 404 comprises identifying eachinput to the target chunk of executable instructions, includingidentifying at least one non-parameter input. For example, the inputsidentification component 118 can identify one or more inputs based ondata identified by the inputs/outputs identification component 114,either during operation of method 400, or prior to operation of method400.

Method 400 also includes an act 405 of recording a snapshot of theinput(s). In some embodiments, act 405 comprises recording acorresponding value for each identified input into a trace, along withinformation identifying the target chunk of executable instructions. Forexample, for each identified input, recording component 119 can obtain avalue for the input (e.g., from memory, from a register, etc.) and storeinto a recorded execution 113 an identification of the inputs (e.g.,memory address, register name, etc.) and a value for the inputs. Inaddition, this snapshot can be stored in the recorded execution 113 in amanner that associates it with the appropriate target chunk ofinstructions. For instance, the recorded execution 113 could include theinstructions themselves, or a reference to the instructions (e.g., byinstruction address, by function or module name, etc.).

As discussed, after recording an inputs snapshot, the target chunk mightbe executed directly. Thus, method 400 might proceed to execute thetarget chunk at the processor(s) 102 (act 406). Alternatively, however,detailed tracing information for the target chunk might be obtained byemulating the target chunk. Thus, method 400 might alternatively proceedto emulate and record the target chunk (act 407).

If method 400 proceeds to act 406 for executing the target chunk, method400 might perform one or more validation and/or recording actions. Forexample, executing the target chunk in act 406 might include one or moreof recording information indicative of output(s) (act 406 a), recordinginformation indicative of processor state (act 406 b), validating viaforking (act 406 c), and/or validating via PTEs (act 406 b).

In act 406 a, the outputs recording component 120 could recordinformation about the output(s) of having executed the target chunk ofinstructions at the processor(s) 102. For instance, the outputsrecording component 120 might record a corresponding value for eachoutput of execution of the target chunk of executable instructions, orrecord one or more hashes based on the corresponding value for eachoutput of the execution of the target chunk of executable instructions.This output information is then usable to validate whether a replayedexecution of the target chunk of executable instructions deviated fromexecution of the target chunk of executable instructions as part of theexecution of the executable entity.

In act 406 b, the processor state recording component 121 could recordprocessor state information usable as a partial trace of the executionof the target chunk of executable instructions. For instance, theprocessor state recording component 121 might record one or more of oneor more snapshots of processor state, one or more hashes of processorstate, a control flow trace (e.g., INTEL's IPT), or one or moreprocessor event based samples (e.g., INTEL's PEBS). This processor stateis then usable to validate whether a replayed execution of the targetchunk of executable instructions deviated from execution of the targetchunk of executable instructions as part of the execution of theexecutable entity.

In act 406 c, the execution validation component 122 could use forkingto validate, at record time, whether or not a replay based on inputssnapshot would produce that same outputs as the execution of the targetchunk at the processor(s) 102. For example, act 406 c could includeforking execution of the executable entity, and executing a forkedtarget chunk of executable instruction. Then, act 406 c could includecomparing outputs of executing the target chunk of executableinstructions with outputs of executing the forked target chunk ofexecutable instructions, to determine if the execution of the forkedtarget chunk of executable instructions deviated from the execution ofthe target chunk of executable instructions.

In act 406 d, the execution validation component 122 could use PTEs tovalidate if another entity interfered with the subject entity. Forexample, the execution validation component 122 could mark one or morePTEs not corresponding to each input to the target chunk of executableinstructions as invalid for the executable entity. Then, based onmarking the one or more PTEs, the execution validation component 122could detect an access by the executable entity and then determine fromthe access that the identified inputs to the target chunk of executableinstructions were incomplete for the target chunk of executableinstructions.

In act 406 d, the execution validation component 122 could additionally,or alternatively, use PTEs to detect if the list of identified inputswas incomplete. For example, the execution validation component 122could mark one or more PTEs not corresponding to each input to thetarget chunk of executable instructions as invalid for the executableentity. Then, based on marking the one or more PTEs, the executionvalidation component 122 could detecting an access by the executableentity and then determine that the identified inputs to the target chunkof executable instructions were incomplete for the target chunk ofexecutable instructions.

Alternatively, if method 400 proceeds to act 407 for emulating andrecording the target chunk, method 400 might include one or more ofpriming a cache with the input(s) (act 407 a) and/or deferring cacheentry validation (act 407 b).

In act 407 a, the emulation component 123 could prime a cache with cacheentries covering each identified input. Then, after priming the cache,the emulation component 123 could emulate execution of the target chunkof executable instructions while recording the emulated execution of thetarget chunk of executable instructions into the trace.

After priming the cache, while emulating the execution of the targetchunk of executable instructions, in act 407 b the emulation component123 could defer validation of one or more primed cache entries with abacking memory until a synchronization event. Then, in connection withreaching the synchronization event, the emulation component 123 mightfully validate each of the primed cache entries with the backing memory,or tag each of the primed cache entries for a lazy validation.

In embodiments, the executable entity might be instrumented to recordeach input to the target chunk of executable instructions. Thus, inmethod 400, the executable entity might generate trace data duringexecution of the target chunk of executable instructions.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the described features or acts described above,or the order of the acts described above. Rather, the described featuresand acts are disclosed as example forms of implementing the claims.

The present invention may be embodied in other specific forms withoutdeparting from its spirit or essential characteristics. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive. The scope of the invention is, therefore, indicatedby the appended claims rather than by the foregoing description. Allchanges which come within the meaning and range of equivalency of theclaims are to be embraced within their scope. When introducing elementsin the appended claims, the articles “a,” “an,” “the,” and “said” areintended to mean there are one or more of the elements. The termscomprising,” “including,” and “having” are intended to be inclusive andmean that there may be additional elements other than the listedelements.

What is claimed:
 1. A method, implemented at a computer system thatincludes at least one processor, for performing a targeted partialrecording of an executable entity, the method comprising: executing theexecutable entity at the at least one processor; while executing theexecutable entity, determining that a target chunk of executableinstructions that is to be executed as part of the execution of theexecutable entity is to be recorded during the execution of theexecutable entity; prior to executing the target chunk of executableinstructions, identifying one or more inputs of the target chunk ofexecutable instructions, including identifying at least onenon-parameter input of the target chunk of executable instructions; andrecording a corresponding value for each identified input into a partialrecording of the execution of the executable entity, along withinformation identifying the target chunk of executable instructions; andafter recording the corresponding value for each identified input,executing the target chunk of executable instructions at the at leastone processor.
 2. The method of claim 1, further comprising recordinginformation usable to validate whether a replayed execution of thetarget chunk of executable instructions deviated from execution of thetarget chunk of executable instructions as part of the execution of theexecutable entity, the information comprising at least one of: acorresponding value for each output of execution of the target chunk ofexecutable instructions; one or more hashes based on the correspondingvalue for each output of the execution of the target chunk of executableinstructions; or a partial trace of the execution of the target chunk ofexecutable instructions, including at least one of: one or moresnapshots of processor state, one or more hashes of processor state, acontrol flow trace, or one or more processor event based samples.
 3. Themethod of claim 1, wherein identifying the one or more inputs of thetarget chunk of executable instructions is based on having performed atleast one of: a static analysis of the target chunk of executableinstructions; a static analysis of a recorded execution of the targetchunk of executable instructions; an emulation of the target chunk ofexecutable instructions; or an analysis of at least one of debuggingsymbols or code annotations.
 4. The method of claim 1, furthercomprising: priming a cache with cache entries covering each identifiedinput; and after priming the cache, emulating execution of the targetchunk of executable instructions while recording the emulated executionof the target chunk of executable instructions into the partialrecording of the execution of the executable entity.
 5. The method ofclaim 4, further comprising, while emulating the execution of the targetchunk of executable instructions, deferring validation of one or moreprimed cache entries with a backing memory until a synchronizationevent.
 6. The method of claim 5, further comprising, in connection withreaching the synchronization event, performing at least one of:validating each of the one or more primed cache entries with the backingmemory; or tagging each of the one or more primed cache entries for alazy validation.
 7. The method of claim 1, further comprising: executingthe target chunk of executable instructions at the at least oneprocessor; forking execution of the executable entity, and executing aforked target chunk of executable instructions; and comparing outputs ofexecuting the target chunk of executable instructions with outputs ofexecuting the forked target chunk of executable instructions, todetermine if the execution of the forked target chunk of executableinstructions deviated from the execution of the target chunk ofexecutable instructions.
 8. The method of claim 1, further comprising:marking one or more page table entries (PTEs) corresponding to the oneor more inputs of the target chunk of executable instructions as invalidfor an executable entity other than the executable entity; and based onmarking the one or more PTEs, detecting an access by the executableentity other than the executable entity; and based on detecting theaccess, determining that the executable entity other than the executableentity interfered with an input of the target chunk of executableinstructions.
 9. The method of claim 1, further comprising: marking oneor more page table entries (PTEs) not corresponding to the one or moreinputs of the target chunk of executable instructions as invalid for theexecutable entity; and based on marking the one or more PTEs, detectingan access by the executable entity; and based on detecting the access,determining that the identified one or more inputs of the target chunkof executable instructions were incomplete for the target chunk ofexecutable instructions.
 10. A computer system comprising: a processor;and a computer-readable medium having stored thereon computer-executableinstructions that are executable by the processor to cause the computersystem to perform a targeted partial recording of an executable entity,the computer-executable instructions including instructions that areexecutable by the processor to cause the computer system to at least:execute the executable entity at the processor; while executing theexecutable entity, determine that a target chunk of executableinstructions that is to be executed as part of the execution of theexecutable entity is to be recorded during the execution of theexecutable entity; prior to executing the target chunk of executableinstructions, identify one or more inputs of the target chunk ofexecutable instructions, including identifying at least onenon-parameter input of the target chunk of executable instructions; andrecord a corresponding value for each identified input into a partialrecording of the execution of the executable entity, along withinformation identifying the target chunk of executable instructions; andafter recording the corresponding value for each identified input,execute the target chunk of executable instructions at the processor.11. The computer system of claim 10, the computer-executableinstructions also including instructions that are executable by theprocessor to cause the computer system to record information usable tovalidate whether a replayed execution of the target chunk of executableinstructions deviated from execution of the target chunk of executableinstructions as part of the execution of the executable entity, theinformation comprising at least one of: a corresponding value for eachoutput of execution of the target chunk of executable instructions; oneor more hashes based on the corresponding value for each output of theexecution of the target chunk of executable instructions; or a partialtrace of the execution of the target chunk of executable instructions,including at least one of: one or more snapshots of processor state, oneor more hashes of processor state, a control flow trace, or one or moreprocessor event based samples.
 12. The computer system of claim 10,wherein identifying the one or more inputs of the target chunk ofexecutable instructions is based on having performed at least one of: astatic analysis of the target chunk of executable instructions; a staticanalysis of a recorded execution of the target chunk of executableinstructions; an emulation of the target chunk of executableinstructions; or an analysis of at least one of debugging symbols orcode annotations.
 13. The computer system of claim 10, thecomputer-executable instructions also including instructions that areexecutable by the processor to cause the computer system to: prime acache with cache entries covering each identified input; and afterpriming the cache, emulate execution of the target chunk of executableinstructions while recording the emulated execution of the target chunkof executable instructions into the partial recording of the executionof the executable entity.
 14. The computer system of claim 13, thecomputer-executable instructions also including instructions that areexecutable by the processor to cause the computer system to, whileemulating the execution of the target chunk of executable instructions,defer validation of one or more primed cache entries with a backingmemory until a synchronization event.
 15. The computer system of claim10, the computer-executable instructions also including instructionsthat are executable by the processor to cause the computer system to:execute the target chunk of executable instructions at the processor;fork execution of the executable entity, and execute a forked targetchunk of executable instructions; and compare outputs of executing thetarget chunk of executable instructions with outputs of executing theforked target chunk of executable instructions, to determine if theexecution of the forked target chunk of executable instructions deviatedfrom the execution of the target chunk of executable instructions. 16.The computer system of claim 10, the computer-executable instructionsalso including instructions that are executable by the processor tocause the computer system to: mark one or more page table entries (PTEs)corresponding to the one or more inputs of the target chunk ofexecutable instructions as invalid for an executable entity other thanthe executable entity; and based on marking the one or more PTEs, detectan access by the executable entity other than the executable entity; andbased on detecting the access, determine that the executable entityother than the executable entity interfered with an input of the targetchunk of executable instructions.
 17. The computer system of claim 10,the computer-executable instructions also including instructions thatare executable by the processor to cause the computer system to: markone or more page table entries (PTEs) not corresponding to the one ormore inputs of the target chunk of executable instructions as invalidfor the executable entity; and based on marking the one or more PTEs,detect an access by the executable entity; and based on detecting theaccess, determine that the identified one or more inputs of the targetchunk of executable instructions were incomplete for the target chunk ofexecutable instructions.
 18. A computer program product comprising ahardware storage device having stored thereon computer-executableinstructions that are executable by a processor to cause a computersystem to perform a targeted partial recording of an executable entity,the computer-executable instructions including instructions that areexecutable by the processor to cause the computer system to at least:execute the executable entity at the processor; while executing theexecutable entity, determine that a target chunk of executableinstructions that is to be executed as part of the execution of theexecutable entity is to be recorded during the execution of theexecutable entity; prior to executing the target chunk of executableinstructions, identify one or more inputs of the target chunk ofexecutable instructions, including identifying at least onenon-parameter input of the target chunk of executable instructions; andrecord a corresponding value for each identified input into a partialrecording of the execution of the executable entity, along withinformation identifying the target chunk of executable instructions;after recording the corresponding value for each identified input intothe partial recording of the execution of the executable entity, executethe target chunk of executable instructions at the processor, andperform at least one of: recording a corresponding value for each outputof execution of the target chunk of executable instructions; recordingone or more hashes based on the corresponding value for each output ofthe execution of the target chunk of executable instructions; recordinga partial trace of the execution of the target chunk of executableinstructions, including at least one of: one or more snapshots ofprocessor state, one or more hashes of processor state, a control flowtrace, or one or more processor event based samples; or forkingexecution of the executable entity, execute a forked target chunk ofexecutable instructions, and compare outputs of executing the targetchunk of executable instructions with outputs of executing the forkedtarget chunk of executable instructions, to determine if the executionof the forked target chunk of executable instructions deviated from theexecution of the target chunk of executable instruction.